Stars
FAIR Chemistry's library of machine learning methods for chemistry
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
py-sc-fermi is a materials modelling code for calculating self-consistent Fermi energies and defect concentrations under thermodynamic equilibrium (or quasi-equilibrium) given defect formation ener…
A Python package for estimating diffusion properties from molecular dynamics simulations.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
DScribe is a python package for creating machine learning descriptors for atomistic systems.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
MAterials Simulation Toolkit for Machine Learning (MAST-ML)
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.